Kennesaw State University was the first university in the country to offer a formal Ph.D. in Analytics and Data Science, with the first students accepted into the program in Fall, 2015. Since then, the Program has maintained an acceptance rate under 10% - making it one of the most competitive graduate programs in the country.
This interdisciplinary research degree trains individuals to translate large, structured and unstructured, complex data into information to facilitate innovation, research, and improved decision making. The curriculum includes heavy emphasis on data structure and capture, algorithm development, graph theory, optimization, machine learning, statistical modeling, and the mathematical foundations to support these concepts. Importantly, the program also emphasizes communication skills - both oral and written - as well as application and tying results to business and research problems. raduates can either pursue a position in the private or public sector as a "practicing" Data Scientist - where continued demand is expected to greatly outpace the supply - or pursue a position within academia, where they would be uniquely qualified to teach these skills to the next generation.
Students engage in relevant and impactful research aligned with the four interdisciplinary research themes established by the Office of Research KSU: Biomedical and Health Services, Computing and Technology, Human Development and Well-Being, and Sustainable and Safe Communities.
We take seriously the responsibility of ethical data science. Our Guiding Ethical Principles are:
PRINCIPLE OF RESPONSIBLE DATA COLLECTION AND SOURCING
Data Scientists have a responsibility to understand how data was collected, ensure the data has been sourced legally and ethically, confirm that use of the data is consistent with how it was intended to be used, and verify that no group(s) of people are intentionally statistically mis/under-represented.
PRINCIPLE OF PROTECTION
Data Scientists have a responsibility to protect and defend integrity of the data entrusted to them.
PRINCIPLE OF TRANSPARENCY and REPRODUCIBILITY
Data Scientists have a responsibility to ensure that the transformation of data into products (e.g., algorithms) is as transparent as possible. The process should be well-documented, explainable, and reproducible.
PRINCIPLE OF FORESIGHT
Data Scientists have a responsibility to provide evidence that any products they have developed do not exhibit bias or potential harm against any demographic subgroups such as race, gender or ethnicity or subgroups defined by genetic markers or socio-economic status.
PRINCIPLE OF COMPETENCE
While Data Scientists come from multiple educational backgrounds, all individuals engaged in the practice of transforming data into analytical products should accurately represent their qualifications, the limits of their expertise and commit to continued education.